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Meta-Analysis
. 2010 Oct;3(5):475-83.
doi: 10.1161/CIRCGENETICS.109.899443. Epub 2010 Oct 5.

Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study: A Genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls

Michael Preuss  1 , Inke R König, John R Thompson, Jeanette Erdmann, Devin Absher, Themistocles L Assimes, Stefan Blankenberg, Eric Boerwinkle, Li Chen, L Adrienne Cupples, Alistair S Hall, Eran Halperin, Christian Hengstenberg, Hilma Holm, Reijo Laaksonen, Mingyao Li, Winfried März, Ruth McPherson, Kiran Musunuru, Christopher P Nelson, Mary Susan Burnett, Stephen E Epstein, Christopher J O'Donnell, Thomas Quertermous, Daniel J Rader, Robert Roberts, Arne Schillert, Kari Stefansson, Alexandre F R Stewart, Gudmar Thorleifsson, Benjamin F Voight, George A Wells, Andreas Ziegler, Sekar Kathiresan, Muredach P Reilly, Nilesh J Samani, Heribert Schunkert; CARDIoGRAM Consortium
Collaborators, Affiliations
Meta-Analysis

Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study: A Genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls

Michael Preuss et al. Circ Cardiovasc Genet. 2010 Oct.

Abstract

Background: Recent genome-wide association studies (GWAS) of myocardial infarction (MI) and other forms of coronary artery disease (CAD) have led to the discovery of at least 13 genetic loci. In addition to the effect size, power to detect associations is largely driven by sample size. Therefore, to maximize the chance of finding novel susceptibility loci for CAD and MI, the Coronary ARtery DIsease Genome-wide Replication And Meta-analysis (CARDIoGRAM) consortium was formed.

Methods and results: CARDIoGRAM combines data from all published and several unpublished GWAS in individuals with European ancestry; includes >22 000 cases with CAD, MI, or both and >60 000 controls; and unifies samples from the Atherosclerotic Disease VAscular functioN and genetiC Epidemiology study, CADomics, Cohorts for Heart and Aging Research in Genomic Epidemiology, deCODE, the German Myocardial Infarction Family Studies I, II, and III, Ludwigshafen Risk and Cardiovascular Heath Study/AtheroRemo, MedStar, Myocardial Infarction Genetics Consortium, Ottawa Heart Genomics Study, PennCath, and the Wellcome Trust Case Control Consortium. Genotyping was carried out on Affymetrix or Illumina platforms followed by imputation of genotypes in most studies. On average, 2.2 million single nucleotide polymorphisms were generated per study. The results from each study are combined using meta-analysis. As proof of principle, we meta-analyzed risk variants at 9p21 and found that rs1333049 confers a 29% increase in risk for MI per copy (P=2×10⁻²⁰).

Conclusion: CARDIoGRAM is poised to contribute to our understanding of the role of common genetic variation on risk for CAD and MI.

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Figures

Figure 1
Figure 1
Workflow of CARDIoGRAM. Analyses are performed in every study separately by the statistical group and then submitted to the central database. The analysis group checks the data quality within each study and queries individual studies on summary data. Once the initial quality control has been performed and data summaries are consistent across individual studies, these quality-controlled data are updated in the database and used for meta-analysis.
Figure 2
Figure 2
Estimated power of the meta-analysis. Power for different MAFs and ORs at a P value of 5×10−8 (n=22 000 cases and 60 000 controls).
Figure 3
Figure 3
Estimated power for the replication. Power for different MAFs and ORs. Critical P value for a 1-sided test, 0.05×2=0.1 adjusted for the testing of 30 regions (n=15 000 cases and 15 000 controls).
Figure 4
Figure 4
Forest plots for SNPs on chromosome 9p21. Random effects (RE) models were calculated for SNPs rs1333049 (risk allele =C), rs2383206 (risk allele=G), and rs10757278 (risk allele=G); the fixed effects (FE) model was calculated for SNP rs10811661 (risk allele=C). Heterogeneity between the studies is indicated by I2, and for every study, it is indicated whether the respective SNP was genotyped (G) or imputed (I) or a mixture of genotyped and imputed (NA).
Figure 5
Figure 5
Results for subgroup association analysis for SNP rs1333049. Shown are ORs with 95% CIs comparing female cases versus female controls, male cases versus male controls, old cases (≥50 years) versus all controls, and young cases (<50 years) versus all controls. Numbers below the x axis denote P values, fixed effects (FE) or random effects (RE) models, and number of cases/controls.
See this image and copyright information in PMC

Comment in

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